Noise prediction of drones in urban environments

Bian, Haoyu; Fattah, Ryu Jahangir; Sun, Yuhao; Zhang, Xin

doi:10.2514/6.2019-2685

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…It will inspire new measurement and post-processing procedures to support noise regulations and the assessment of the noise impact on communities [37,38]. For instance, this can be achieved by including BPFM aspects in realistic auralizations of rotorcraft noise [20,39] and future noise prediction tools [21,[40][41][42].…”

Section: B Present Contribution and Outlinementioning

confidence: 99%

Low-Frequency Intensity Modulation of High-Frequency Rotor Noise

Baars

Ragni

2023

AIAA AVIATION 2023 Forum

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Acoustic spectra of rotor noise yield frequency-distributions of energy within pressure time series. However, they are unable to reveal phase-relations between different frequency components, while the latter play a role in low-frequency intensity modulation of higherfrequency rotor noise. Baars et al. (AIAA Paper 2021-0713) outlined a methodology to quantify inter-frequency modulation, which in the current work is applied to a comprehensive acoustic dataset of a rotor operating at low Reynolds number at advance ratios ranging from 𝐽 = 0 to 0.61. The findings strengthen earlier observations for the case of a hovering rotor, in which the modulation of the high-frequency noise is strongest at angles of 𝜃 ≈ −20 • (below the rotor plane). For the non-zero advance ratios, modulation becomes dominant in the sector −45 • ≲ 𝜃 ≲ 0 • , and is maximum in strength for the highest advance ratio tested (𝐽 = 0.61). Intensity-modulation of high-frequency noise is primarily the consequence of a far-field observer experiencing a cyclic sweep through the noise directivity patterns of the relatively directive trailing-edge/shedding noise component. This noise becomes more intense with increasing J and is associated with the broadband features of the (partially) separated flow over the rotor blades.

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Section: B Present Contribution and Outlinementioning

confidence: 99%

Low-Frequency Intensity Modulation of High-Frequency Rotor Noise

Baars

Ragni

2023

AIAA AVIATION 2023 Forum

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“…The impact of drone noise during hovering operations in large outdoor urban environments has been explored using acoustic ray tracing. The ground reflection and acoustic refraction by an inhomogeneous atmosphere were included in the sound propagation model [ 22 ].…”

Section: Framework For the Drone Operations Requirementsmentioning

confidence: 99%

“…Two main assumptions have been considered in this paper for the selection of the propagation modifying factors. Firstly, the drone is a single-point sound source propagating with spherical spreading characteristics [ 19 , 22 ], and the operation of the drone’s electric motors generates a significant noise with high-frequency components which, unlike the acoustic signature of typical aircraft noise, reach the receiver without significant attenuation due to drones operating at shorter source/receiver distances [ 20 ]. The spherical sound field can be calculated from the sound power level of the source, considering the geometrical attenuation due to spherical spreading and the attenuation associated with atmospheric absorption [ 25 ].…”

Section: Framework For the Drone Operations Requirementsmentioning

confidence: 99%

Requirements for Drone Operations to Minimise Community Noise Impact

Ramos-Romero

Green

Roberts

et al. 2022

IJERPH

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The number of applications for drones under R&D have growth significantly during the last few years; however, the wider adoption of these technologies requires ensuring public trust and acceptance. Noise has been identified as one of the key concerns for public acceptance. Although substantial research has been carried out to better understand the sound source generation mechanisms in drones, important questions remain about the requirements for operational procedures and regulatory frameworks. An important issue is that drones operate within different airspace, closer to communities than conventional aircraft, and that the noise produced is highly tonal and contains a greater proportion of high-frequency broadband noise compared with typical aircraft noise. This is likely to cause concern for exposed communities due to impacts on public health and well-being. This paper presents a modelling framework for setting recommendations for drone operations to minimise community noise impact. The modelling framework is based on specific noise targets, e.g., the guidelines at a receiver position defined by WHO for sleep quality inside a residential property. The main assumption is that the estimation of drone noise exposure indoors is highly relevant for informing operational constraints to minimise noise annoyance and sleep disturbance. This paper illustrates the applicability of the modelling framework with a case study, where maximum A-weighted sound pressure levels LAmax and sound exposure levels SEL as received in typical indoor environments are used to define drone-façade minimum distance to meet WHO recommendations. The practical and scalable capabilities of this modelling framework make it a useful tool for inferring and assessing the impact of drone noise through compliance with appropriate guideline noise criteria. It is considered that with further refinement, this modelling framework could prove to be a significant tool in assisting with the development of noise metrics, regulations specific to drone operations and the assessment of future drone operations and associated noise.

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“…36 Finally, BPF modulation aspects are critical for achieving realistic auralizations of rotorcraft noise, 37 and likewise, BPF modulation characteristics will benefit future extensions of noise prediction tools. [38][39][40][41]…”

Section: B Present Contribution and Outlinementioning

confidence: 99%

Quantifying modulation in the acoustic field of a small-scale rotor using bispectral analysis

Baars

Bullard

Mohamed

2021

AIAA Scitech 2021 Forum

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This paper describes a methodology to quantify inter-frequency modulation in the acoustic field of a small-scale rotor. How the blade passing frequency modulates the intensity of the higher-frequency (broadband) noise content is of specific interest, as this modulation is a major factor in the human perception of rotor noise from advanced air mobility vehicles and drones. A proposed modulation-parameter is based on post-processing steps that are applicable to a single acoustic time series. First, an auto-bispectral analysis assesses the dominant nonlinear, quadratic inter-frequency coupling between the blade passing frequency and the higher-frequency noise content. Secondly, the degree of modulation is determined using a robust parameter: a correlation parameter between the (low-frequency) modulating BPF signal and an envelope of the (higher-frequency) carrier signal. Provided that a single parameter is obtained for a given acoustic time series, the directivity pattern of the modulation strength can be inferred from data available from standard acoustic measurement campaigns. For illustration, an 11 inch diameter single-rotor in hover is considered, with acoustic data taken at 420 microphone positions within a plane perpendicular to the rotor disk. It is revealed that modulation is confined to a sector θ ≈ (10 • , −45 • ), where θ = 0 • is the rotor plane and negative angles are in the direction of the rotor-induced flow. The strongest modulation appears around θ ≈ −15 • . This work aids in quantifying the phenomenological description of modulation, namely that it results from the periodic advance and retreat of certain rotor blade's noise sources, relative to a stationary observer.

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Noise prediction of drones in urban environments

Cited by 10 publications

References 19 publications

Low-Frequency Intensity Modulation of High-Frequency Rotor Noise

Low-Frequency Intensity Modulation of High-Frequency Rotor Noise

Requirements for Drone Operations to Minimise Community Noise Impact

Quantifying modulation in the acoustic field of a small-scale rotor using bispectral analysis

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